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A State-Space Model For Prototype Learning

Abstract

A general state-space model of prototype learning was formulated Interms of a set of Internal states and nonlinear Input-output mappings. The general model Includes several previous models as special cases such as Hintzman's (1986) multiple trace model, Metcalf's (1982) holographic model,and two parallel distributive memory models (Knapp & Anderson, 1984;McClelland & Rumelhart, 1985). Two basic properties common to the threemodels were defined in terms of this general model--addltivlty and time Invarlance. An experiment was conducted to test the basic properties using random spectral patterns as stimuli allowing possible nonlinear input and output distortions. Especially, ordinal tests of addltivlty were performed with few assumptions about Internal features that subjects may use to encode the stimulus Information. The results support addltivlty but tlme-Invarlance was clearly violated. Implications of these findings for models of the human memory system are discussed.

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